Peer-citable research on AI agent memory systems, behavioral contracts, and supply chain security.
Varun Pratap Bhardwaj, 2026
DOI: 10.5281/zenodo.18709670
Presents a local-first memory architecture for AI agents with formal Bayesian trust scoring that defends against OWASP ASI06 memory poisoning — without cloud dependencies or LLM inference calls.
Varun Pratap Bhardwaj, 2026
DOI: 10.5281/zenodo.18775393
Introduces Agent Behavioral Contracts (ABC), adapting Design-by-Contract principles to AI agents with probabilistic compliance metrics and drift bounds. Tested across 1,980 sessions on seven models.
Varun Pratap Bhardwaj, 2026
DOI: 10.5281/zenodo.18787663
Addresses security vulnerabilities in AI skill ecosystems with formal verification — achieving F1=96.95% with 100% precision and 0% false positives on a 540-skill benchmark.
@misc{bhardwaj2026superlocalmemory,
title = {SuperLocalMemory: Privacy-Preserving Multi-Agent Memory
with Bayesian Trust Defense Against Memory Poisoning},
author = {Bhardwaj, Varun Pratap},
year = {2026},
doi = {10.5281/zenodo.18709670},
url = {https://zenodo.org/records/18709670}
}
@article{bhardwaj2026agentbehavioral,
title = {Agent Behavioral Contracts: Formal Specification and
Runtime Enforcement for Reliable Autonomous AI Agents},
author = {Bhardwaj, Varun Pratap},
year = {2026},
eprint = {2602.22302},
archivePrefix = {arXiv},
primaryClass = {cs.AI},
url = {https://arxiv.org/abs/2602.22302}
}
@misc{bhardwaj2026skillfortify,
title = {SkillFortify: Formal Analysis and Supply Chain Security
for Agentic AI Skills},
author = {Bhardwaj, Varun Pratap},
year = {2026},
doi = {10.5281/zenodo.18787663},
url = {https://zenodo.org/records/18787663}
}
Whether you are working on memory systems, agent reliability, or AI security, we are open to collaboration.